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Calculates the multi-dimensional SSR model
ssrnd2(X, Y, mdl=NULL, k=NULL, fn=NULL, n_l1=NULL, iter=1000, eps=0.0001)
data list with the relevant model data.
matrix with n-dimensional coordinates.
array with observations.
optional: model from previous training.
optional: maxumum run length for the model.
optional: quantile for partial sums.
optional: subset size for L1 curvature calculation.
optional: number of iterations for the numeric solver.
optional: delta for ending calculation iteration.
Dr. Lars Metzner
Dr. Lars Metzner (2021) Adäquates Maschinelles Lernen. Independently Published.
# \donttest{ # generate data set.seed(1234) x <- rnorm(400) y <- rnorm(400) z <- rnorm(400) + atan2(x, y) X <- matrix(cbind(x, y), ncol = 2) Y <- as.double(z) # Training mdl <- ssrnd2(X, Y) # }
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